DBMS > Couchbase vs. Sphinx vs. Weaviate vs. XTDB

System Properties Comparison Couchbase vs. Sphinx vs. Weaviate vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Open source search engine for searching in data from different sources, e.g. relational databases

An AI-native realtime vector database engine that integrates scalable machine learning models.

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.couchbase.com

sphinxsearch.com

github.com/weaviate/weaviate
weaviate.io

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.couchbase.com

sphinxsearch.com/docs

weaviate.io/developers/weaviate

www.xtdb.com/docs

Developer

Couchbase, Inc.

Sphinx Technologies Inc.

Weaviate B.V.

Juxt Ltd.

Initial release

2011

2001

2019

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

3.5.1, February 2023

1.19, May 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

GPL version 2, commercial licence available

Open Source

commercial license available with Weaviate Enterprise

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Go and Erlang

C++

Clojure

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

yes, maps to GraphQL interface

schema-free

Typing

predefined data types such as float or date

yes

string, int, float, geo point, date, cross reference, fuzzy references

yes, extensible-data-notation format

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

full-text index on all search fields

yes

all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

yes

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-like query language (SphinxQL)

GraphQL is used as query language

limited SQL, making use of Apache Calcite

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

Proprietary protocol

GraphQL query language
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

JavaScript / TypeScript
Python

Clojure
Java

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

Triggers

yes

via the TAP protocol

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

none

yes

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Ephemeral buckets

yes

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
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Key customers

All companies that have data.
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Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
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Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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